Seeing is Not Always Believing: An Empirical Analysis of Fake Evidence Generators

Online scams pose a growing threat to the cyberspace, with cybercriminals frequently using fake evidence, such as identification and financial documents, to illicitly elevate their credibility in online activities. This deceptive trend is fueled by an emerging set of fake evidence generators (FEGens). These FeGensreplicate the output of authoritative sources, such as official bank applications, to automatically generate large quantities of authentic-looking fake evidence. To the best of our knowledge, FeGens,as effective tools for cybercriminals, have not been systematically analyzed in terms of their supply chain, including development, promotion, and delivery, as well as the risks and impacts they pose to end users. In this paper, we present the first systematic empirical analysis of FegEnsand related fake evidence. Our findings shed light on the FegEn ecosystem, particularly the tactics employed by FegEndevelopers and retailers to mimic authoritative sources and promote the use of FeGens. We also evaluate the effectiveness of FeGensand associated risks in cybercrime.